R package for calculating topological characteristics of weighted networks
Version 0.1.2
An example of measuring small-worldness of a weighted network:
# Create an exemplar network in edgelist
edg <- rbind(c(1,2,4), c(1,3,2), c(2,1,4), c(2,3,4),
c(2,4,1), c(2,5,2), c(3,1,2), c(3,2,4),
c(4,2,1), c(5,2,2), c(5,6,1), c(6,5,1))
# Convert the edgelist into an adjacency matrix
adj <- edgelist.to.adjacency(edg)
# Calculate the small-worldness of the network
smallworldness(adj)
# Result
am
1.146284
An example of measuring centralisations a weighted network:
# Create an exemplar network in edgelist
edg <- rbind(c(1,2,4), c(1,3,2), c(2,1,4), c(2,3,4),
c(2,4,1), c(2,5,2), c(3,1,2), c(3,2,4),
c(4,2,1), c(5,2,2), c(5,6,1), c(6,5,1))
# Calculate various centralisations of the network
centr.betweenness(edg)
[1] 0.75
centr.closeness(edg)
[1] 0.5044942
centr.degree(edg)
[1] 0.6666667
centr.strength(edg)
[1] 0.4130435
Examples of ploting degree distribution and strenght distribution of weighted networks:
g <- barabasi.game(1000, directed = FALSE)
edg <- get.edgelist(g)
degree.dist(edg)
[,1] [,2]
[1,] 0 0.596
[2,] 1 0.203
[3,] 2 0.089
[4,] 3 0.045
[5,] 4 0.020
[6,] 5 0.015
[7,] 6 0.002
[8,] 7 0.010
[9,] 8 0.006
[10,] 9 0.003
[11,] 10 0.001
[12,] 11 0.001
[13,] 12 0.001
[14,] 13 0.004
[15,] 14 0.001
[16,] 17 0.001
[17,] 26 0.001
[18,] 29 0.001
degree.dist.plot(edg)
(Intercept) log(degree)
-1.592286 -1.840652
![alt text](https://github.com/hangxiong/wNetwork/blob/master/Degree_Distribution.png "Degree Distribution")
g <- barabasi.game(1000, directed = FALSE)
edg <- get.edgelist(g)
edg = cbind(edg, runif(nrow(edg), 0, 1))
strength.dist(edg)
[,1] [,2]
[1,] 0 0.721
[2,] 1 0.176
[3,] 2 0.058
[4,] 3 0.020
[5,] 4 0.011
[6,] 5 0.006
[7,] 7 0.003
[8,] 8 0.001
[9,] 9 0.002
[10,] 11 0.001
[11,] 14 0.001
strength.dist.plot(edg)
(Intercept) log(strength)
-1.603872 -2.170544
![alt text](https://github.com/hangxiong/wNetwork/blob/master/Strength_Distribution.png "Strength Distribution")
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